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Record W2942612562 · doi:10.1029/2018jc014805

Variations in Rates of Biological Production in the Beaufort Gyre as the Arctic Changes: Rates From 2011 to 2016

2019· article· en· W2942612562 on OpenAlexafffund
Brenda Y. Ji, Zoe O. Sandwith, William J. Williams, Oana Diaconescu, Rubao Ji, Yun Li, Emma Van Scoy, Michiyo Yamamoto‐Kawai, Sarah Zimmermann, Rachel H. R. Stanley

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsFisheries and Oceans Canada
FundersDivision of Ocean SciencesNational Science Foundation of Sri LankaWoods Hole Oceanographic InstitutionFisheries and Oceans CanadaWellesley College
KeywordsArcticEnvironmental scienceOceanographySea iceOcean gyreLatitudeProductivityTundraEcosystemPrimary productionClimate changeMarine ecosystemNew productionOcean acidificationAtmospheric sciencesNutrientEcologyGeologyBiologySubtropics

Abstract

fetched live from OpenAlex

Abstract The Arctic Ocean is experiencing profound environmental changes as the climate warms. Understanding how these changes will affect Arctic biological productivity is key for predicting future Arctic ecosystems and the global CO 2 balance. Here we use in situ gas measurements to quantify rates of gross oxygen production (GOP, total photosynthesis) and net community production (NCP, net CO 2 drawdown by the biological pump) in the mixed layer in summer or fall from 2011 to 2016 in the Beaufort Gyre. NCP and GOP show spatial and temporal variations with higher values linked with lower concentrations of sea ice and increased upper ocean stratification. Mean rates of GOP range from 8 ± 1 to 54 ± 9 mmol O 2 ·m −2 ·d −1 with the highest mean rates occurring in summer of 2012. Mean rates of NCP ranged from 1.3 ± 0.2 to 2.9 ± 0.5 mmol O 2 ·m −2 ·d −1 . The mean ratio of NCP/GOP, a measure of how efficiently the ecosystem is recycling its nutrients, ranged from 0.04 to 0.17, similar to ratios observed at lower latitudes. Additionally, a large increase in total photosynthesis that occurred in 2012, a year of historically low sea ice coverage, persisted for many years. Taken together, these data provide one of the most complete characterizations of interannual variations of biological productivity in this climatically important region, can serve as a baseline for future changes in rates of production, and give an intriguing glimpse of how this region of the Arctic may respond to future lack of sea ice.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.320
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations23
Published2019
Admission routes2
Has abstractyes

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